<html>
<head>
<style type="text/css" media="all">
  @import "css.css" ;
</style>
</head>
<body>
<h2>Example applications and input files for OntoFUNC</h2>
<h3>1. Identify classes of chemicals modulating a pathway</h3>
<p><em>Description:</em>
  The <a target="_blank" href="http://www.ebi.ac.uk/chebi/">Chemical Entities of
  Biological Interest</a> (ChEBI) ontology provides a classification
  of chemicals based on their structure. Based on known interactions
  of chemicals with genes or proteins, we are interested in finding
  classes of chemicals that can modulate a biological pathway, in
  particular pathways known to be affected in diseases (disease
  pathways) or pharmacogenomic pathways.</p>
<p><em>Original dataset:</em> 
  <a target="_blank" href="http://www.pharmgkb.org/pathway/PA2042">Sympathetic
  Nerve Pathway (Neuroeffector Junction)</a> and
  its <a target="_blank" href="http://www.pharmgkb.org/pathway/PA2042#tabview=tab1&subtab=">participants</a>,
  taken from the <a target="_blank" href="http://www.pharmgkb.org">Pharmacogenomics
  Knowledge Base</a>.</p>
<p><em>Protocol:</em>
  Identify for a set of chemicals their target genes/proteins. If the
  chemical targets a gene or protein which is participating in the
  pathway, the chemical is of interest, otherwise it is not of
  interest. A detailed description of the method is available
  <a href="http://bioinformatics.oxfordjournals.org/content/28/16/2169.long" target="_blank">here</a>.</p>
<p><em>OntoFUNC input file:</em> <a href="examples/PA2042">PA2042</a></p>
<p><em>OntoFUNC test:</em> hypergeometric test</p>
<p><em>Ontology:</em> Chemical Entities of Biological Interest (ChEBI)</p>

<h3>2. Identify abnormal phenotype differences between populations </h3>

<p><em>Description:</em>
  The <a target="_blank" href="http://www.human-phenotype-ontology.org/">Human 
Phenotype Ontology</a> (HPO) is an ontology characterizing abnormal
  and clinical phenotypes and can be associated with diseases, e.g., 
  the diseases in <a target="_blank" href="http://omim.org/">OMIM</a>. The <a href="http://hudine.neu.edu/">Human 
  Disease Network</a> (<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000353">Hidalgo CA, Blumm N,
Barabasi A-L, Christakis NA. PLoS Computational Biology, 5(4):e1000353</a>) contains information on co-morbidity between diseases in different populations.
  We can use the HPO to identify <em>clinical phenotypes</em> that are significantly different between
  two populations.
<p><em>Original dataset:</em> 
  <a target="_blank" href="http://barabasilab.neu.edu/projects/hudine/resource/data/data.html">HuDiNe ICD9 5 digit data</a> for
  <em>Black</em> and <em>White</em> populations.
</p>

<p><em>Protocol:</em>
  Normalize occurrence data by the number of patients observed in the
  whole
  dataset. Identify <a href="http://do-wiki.nubic.northwestern.edu/do-wiki/index.php/Main_Page">Human
  Disease Ontology</a> classes corresponding to ICD codes in HuDiNe. Identify HPO phenotypes
  for each disease contained in the HuDiNe dataset. Use OntoFUNC over HPO to perform a binomial test comparing phenotypes in both
  populations.
</p>

<p><em>OntoFUNC input file:</em> <a href="examples/black-white.txt">black-white.txt</a></p>
<p><em>OntoFUNC test:</em> bionomial test</p>
<p><em>Ontology:</em> Human Phenotype Ontology (HP)</p>

<h3>3. Analysis of gene expression data with the Neuro Behavior
  Ontology</h3>
<p><em>Description:</em> The <a href="http://behavior-ontology.googlecode.com">Neuro Behavior
  Ontology</a> (NBO) is an ontology of behavioral processes and
  phenotypes, extending the <tt>behavioral process</tt> branch of the
  Gene Ontology. Annotations to NBO are available from
  the <a href="http://rgd.mcw.edu/">Rat Genome Database</a>, and
  several annotations exist for mouse genes. It therefore becomes
  possible to analyze gene expression datasets using the NBO to reveal
  detailed information about behavioral differences resulting from
  differential expression of genes involved in behavioral processes.
</p>
<p><em>Original
  dataset:</em> <a href="http://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GDS2815">Morphine
    effect on the striatum</a>, Gene Expression Omnibus
  accession <tt>GDS2815</tt></p>
<p><em>Protocol:</em> We import the dataset into R and perform a
  t-test to compute differential expression for each probe id
  between <tt>control</tt> and <tt>chronic morphin use</tt>. We
  subsequently map probe ids to MGI gene identifiers. No correction
  for multiple testing is performed because the results are intended
  for use in a Wilcoxon rank test which is based on the ranks of the
  p-values for differential expression and not on their absolute
  values or sets of genes that are differentially expressed.</p>
<p><em>OntoFUNC input
    file:</em> <a href="examples/GDS2815-func-wilcox.txt">GDS2815-func-wilcox.txt</a></p>
<p><em>OntoFUNC test:</em> Wilcoxon test</p>
<p><em>Ontology:</em> Neuro Behavior Ontology (NBO)</p>

</body>
</html>
